For users only interested in the direct or forward model for radiance simulations the TL/AD/K routines are not required.

For users only interested in the direct or forward model for radiance simulations the TL/AD/K routines are not required.

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//**Atmospheric profiles and other essential items respected with RTTOV**//

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//**Atmospheric profiles and other important quantities respected with RTTOV**//

Temperature (mandatory), variable gas concentrations, cloud and surface properties (all referred to as the state vector, see above). The only mandatory variable gas is water vapour. Optionally ozone, carbon dioxide, nitrous oxide, methane and carbon monoxide can be variable with all other constituents assumed to be constant.

Temperature (mandatory), variable gas concentrations, cloud and surface properties (all referred to as the state vector, see above). The only mandatory variable gas is water vapour. Optionally ozone, carbon dioxide, nitrous oxide, methane and carbon monoxide can be variable with all other constituents assumed to be constant.

RTTOV contains a fast model of the transmittances of the atmospheric gases that is generated from accurate line-by-line transmittances (GENLN2 / kCarta / LBLRTM, or Liebe-89 MPM, resp.) for a set of diverse atmospheric profiles (43L TIGR profile dataset / t101L 52 profile ERA-40 dataset) over the wave-number range of specific channels/instruments in question. The monochromatic transmittances are convolved with the appropriate spectral response functions and are used to compute channel-specific regression coefficients by use of a selected set of predictors. These regression coefficients can then be used by a fast transmittance model to compute transmittances given any other input profile. This parameterization of the transmittances makes the model computationally efficient and in principle should not add significantly to the errors generated by uncertainties in the spectroscopic data used by the line-by-line model. Assessing accuracy by means of comparing computations, e.g., for all the narrow channels of instrument ATOVS see www.metoffice.gov.uk/research/nwp/satellite/rtm/rttov_accuracy.html (as at 6 May 2008). The plot shows the accuracy of the RTTOV-6 and earlier RTTOV-5 model calculations for NOAA-15 ATOVS by comparing them with calculations by an accurate line-by-line model for a diverse set of different atmospheric profiles.

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RTTOV contains a fast model of the transmittances of the atmospheric gases that is generated from accurate line-by-line or continuum transmittances, resp., (GENLN2 / kCarta / LBLRTM; Liebe-89 MPM) for a set of diverse atmospheric profiles (43L TIGR profile dataset / t101L 52 profile ERA-40 dataset) over the wave-number range of specific channels/instruments in question. The monochromatic transmittances are convolved with the appropriate spectral response functions and are used to compute channel-specific regression coefficients by use of a selected set of predictors. These regression coefficients can then be used by a fast transmittance model to compute transmittances given any other input profile. (More detailed description see: www.metoffice.gov.uk/research/nwp/satellite/rtm/rt_lbl.html, as at 6 May 2008.) This parameterization of the transmittances makes the model computationally efficient and in principle should not add significantly to the errors generated by uncertainties in the spectroscopic data used by the line-by-line model. Assessing accuracy by means of comparing computations, e.g., for all the narrow channels of instrument ATOVS see www.metoffice.gov.uk/research/nwp/satellite/rtm/rttov_accuracy.html (as at 6 May 2008). The plot shows the accuracy of the RTTOV-6 and earlier RTTOV-5 model calculations for NOAA-15 ATOVS by comparing them with calculations by an accurate line-by-line model for a diverse set of different atmospheric profiles (noise equivalent temperature difference).

The accuracy of simulating very broad channels (e.g. SEVIRI channel 4 at 3.9 microns) is addressed to be poor, here significant bias can occur.

The accuracy of simulating very broad channels (e.g. SEVIRI channel 4 at 3.9 microns) is addressed to be poor, here significant bias can occur.

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So, it is important to state that the primary goal of RTTOV is very fast computing RT for pre-calculated fixed channels of instruments, but with atmospheric profiles and additionals (surface and cloud items, zenith angles etc.) relatively free in choice.

So, it is important to state that the primary goal of RTTOV is very fast computing RT for pre-calculated fixed channels of instruments, but with atmospheric profiles and additionals (surface and cloud items, zenith angles etc.) relatively free in choice.

rttov.1210245762.txt.gz · Last modified: 2008/05/08 12:22 by pa25
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